Welcome to CUDA: Week In Review
News and resources for the worldwide GPU and parallel programming community. |
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CUDA PRO TIP |
| Learn about the performance implications of the Tail Effect and how to work around it on the Parallel Forall Blog. |
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CUDA SPOTLIGHT |
 GPU-Accelerated Nanotechnology
This week's Spotlight is on Dr. Mark Bathe, associate professor of biological engineering at the Massachusetts Institute of Technology. Mark's lab focuses on in silico design and programming of synthetic nucleic acid scaffolds.
Mark comments: "GPU computing plays a major enabling role in diverse aspects of our technology developments." Read the Spotlight. |
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CUDA NEWS |
Stanford Launches the HIVE
Stanford University announced the HIVE, a state-of-the-art facility for scientific visualization in the Huang Engineering Center.
"Researchers are creating tremendous amounts of data through computations, simulations, measurements, sensor readings and so forth. We have to have a way to visualize such data in ways that allow us to see the big picture and also zoom in on the detail," said Dr. Margot Gerritsen, director of Stanford's Institute for Computational and Mathematical Engineering (ICME).
The HIVE consists of 35 high-definition displays, synched with NVIDIA technology, that can work together to offer a detailed view of one image, or display side-by-side visualizations of different images.
New Image & Signal Processing Research
Solutions provider SagivTech collaborated with the University of Bremen (Germany), EPFL (Switzerland) and others on the UNLoCX project. Funded by the European Commission, UNLoCX conducted numerical experiments with mass spectrometry imaging data on GPUs, reducing processing times from several hours to several minutes. The goal is to tackle complex applications in life sciences and ultra-precise audio signal processing which presently cannot be solved appropriately with existing algorithms. The results are described in a paper recently published in Advances in Computational Mathematics (June 2014). |
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UPCOMING GPU WEBINARS |
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July 16: GPU Architecture & the CUDA Memory Model, C. Mason, Acceleware
July 22: GPU Computing with MATLAB, D. Doherty, MathWorks
Aug. 12: Asynchronous Operations & Dynamic Parallelism in CUDA, D. Cyca, Acceleware |
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UPCOMING GPU MEETUPS |
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June 16: Silicon Valley
June 26: Brisbane, Australia
June 30: Riga, Latvia
July 10: Singapore |
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NEW ON THE BLOG |
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Parallel Forall:
Drop-in Acceleration of GNU Octave, N. Markovsky
CUDA Pro Tip: Minimize the Tail Effect, J. Demouth
Accelerating a C++ CFD code with OpenACC, J. Kraus
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CUDA CALENDAR |
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JUNE
ISCA ’14 (Symposium on Computer Architecture)
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June 14-18, 2014, Minneapolis, Minn.
(OpenCV + GPU tutorial on June 15, chaired by Dan Connors, Univ. of Colorado, with keynote by Steve Keckler, NVIDIA) |
Intro to GPGPU Programming (VSCSE/XSEDE)
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June 16-20, 2014
(Virtual course delivered at multiple locations) |
4-Day GPU Computing Course (SagivTech)
ISC ’14
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June 22-26, 2014, Leipzig, Germany |
HPDC ’14
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June 23-27, 2014, Vancouver, Canada |
HPC Workshop: Summer Bootcamp (XSEDE)
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June 24-27, 2014
(Virtual course delivered at multiple locations) |
4-Day CUDA Course (Acceleware)
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June 24-27, 2014, San Jose, Calif. |
JULY
GPU Tech Workshop Taiwan (NVIDIA)
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July 8, 2014, Taipei, Taiwan |
GPU Tech Workshop SE Asia (NVIDIA)
Programming Heterogeneous Systems in Physics (Workshop)
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July 14-15, 2014, Jena, Germany |
GPU Tech Conference Japan (NVIDIA)
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July 16, 2014, Tokyo, Japan |
GPUs and Scientific Applications (University of Alicante)
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July 21-24, 2014, Alicante, Spain |
CUDA Programming Course (Oxford University)
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July 21-25, 2014, Oxford, UK
Instructor: Mike Giles |
HPCS 2014
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July 21-25, 2014, Bologna, Italy |
(To list an event, email: cuda_week_in_review@nvidia.com) |
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CUDA RESOURCES |
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Online Learning |
| Udacity | Coursera | APC Russia |
GPU-Accelerated Libraries |
| Adding GPU acceleration to an application can be as easy as calling a library function. Check out these high-performance libraries from NVIDIA and partners. |
CUDA Consulting |
| Training, programming and project development services are available from CUDA consultants around the world.
To be considered for inclusion on list, email: cuda_week_in_review@nvidia.com. |
GPU Test Drive |
| Want to try Tesla K40 for free? Sign up here. |
CUDACasts |
| Check out our new series of short videos about CUDA. |
Tell Us Your CUDA Story |
| If you are a CUDA developer, tell us how you are using CUDA. |
GPU-Accelerated Apps |
| See updated list of 270+ GPU-accelerated applications. |
GPU Meetups |
| Learn about Meetups in your city, or start one up. |
CUDA Documentation |
| The CUDA documentation site includes release notes,
programming guides, manuals and code samples. |
NVIDIA Developer Forums |
| Join us on the NVIDIA DevTalk forums to share your experience and learn from other developers.
You can also ask questions on Stack Overflow,
using the ’cuda’ tag. |
GPU Computing on Twitter |
| For daily updates about GPU computing and parallel programming, follow @gpucomputing on Twitter. |
Downloads |
CUDA
Nsight |
CUDA on the Web |
CUDA Spotlights
CUDA Newsletters
CUDA Zone
GPU Test Drive
GPUComputing.net
GPGPU.org
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NVIDIA Newsletters |
Sign up for NVIDIA Newsletters, including Media & Entertainment, GeForce, NVIDIA GRID VDI and Shield.
Please fill out our reader survey so we can improve in 2014. Thanks! |
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ABOUT CUDA |
CUDA® is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).
NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++ and Fortran.
Send comments to cuda_week_in_review@nvidia.com
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 Copyright © 2014 NVIDIA Corporation. All rights reserved. 2701 San Tomas Expressway, Santa Clara, CA 95050. |
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